A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control

In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation prob...

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Main Authors: David Navarro-Alarcon, Jiaming Qi, Jihong Zhu, Andrea Cherubini
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Neurorobotics
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fnbot.2020.00059/full
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author David Navarro-Alarcon
Jiaming Qi
Jihong Zhu
Andrea Cherubini
author_facet David Navarro-Alarcon
Jiaming Qi
Jihong Zhu
Andrea Cherubini
author_sort David Navarro-Alarcon
collection DOAJ
description In this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialize in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method.
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spelling doaj.art-319e9038d76942f4a370837c08f40f212022-12-21T23:33:59ZengFrontiers Media S.A.Frontiers in Neurorobotics1662-52182020-09-011410.3389/fnbot.2020.00059550099A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based ControlDavid Navarro-Alarcon0Jiaming Qi1Jihong Zhu2Andrea Cherubini3The Hong Kong Polytechnic University, Hong Kong, Hong KongThe Hong Kong Polytechnic University, Hong Kong, Hong KongUniversité de Montpellier/LIRMM, Montpellier, FranceUniversité de Montpellier/LIRMM, Montpellier, FranceIn this article, we present a new scheme that approximates unknown sensorimotor models of robots by using feedback signals only. The formulation of the uncalibrated sensor-based regulation problem is first formulated, then, we develop a computational method that distributes the model estimation problem amongst multiple adaptive units that specialize in a local sensorimotor map. Different from traditional estimation algorithms, the proposed method requires little data to train and constrain it (the number of required data points can be analytically determined) and has rigorous stability properties (the conditions to satisfy Lyapunov stability are derived). Numerical simulations and experimental results are presented to validate the proposed method.https://www.frontiersin.org/article/10.3389/fnbot.2020.00059/fullroboticssensorimotor modelsadaptive systemssensor-based controlservomechanismsvisual servoing
spellingShingle David Navarro-Alarcon
Jiaming Qi
Jihong Zhu
Andrea Cherubini
A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
Frontiers in Neurorobotics
robotics
sensorimotor models
adaptive systems
sensor-based control
servomechanisms
visual servoing
title A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
title_full A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
title_fullStr A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
title_full_unstemmed A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
title_short A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control
title_sort lyapunov stable adaptive method to approximate sensorimotor models for sensor based control
topic robotics
sensorimotor models
adaptive systems
sensor-based control
servomechanisms
visual servoing
url https://www.frontiersin.org/article/10.3389/fnbot.2020.00059/full
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